Geng Chen

@gengchen

Ph.D. student at UPenn @GRASPlab | Prev Master student @UCSDJacobs, Undergrad @sjtu1896 | Working on Embodied AI & Robot Learning.

San Diego, CA

jc043.github.io

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Geng Chen
@gengchen
Mar 15, 2025
Can we build a robot policy foundation model🤖 that incorporates 3D observations? 🚀Introducing FP3, a first 3D foundation policy for robotic manipulation. Using only 80 demonstrations, FP3 can solve a new task with over 90% success rates in the wild! Let's dive in! 🧵1/N
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Geng Chen
@gengchen
Jun 2
Excited to announce that FP3 has been selected as an ICRA 2026 Best Paper Award Finalist on Robot Learning! 🎉 Unfortunately, I won’t be able to attend in person in Vienna, but our advisor @gao_young will be presenting the work today. Please stop by if you are at ICRA! 📍
Geng Chen
@gengchen
Feb 1
Glad to share that our paper FP3 has been accepted to #ICRA2026! 🎉Huge thanks to my co-authors and collaborators, it's been a long ride. In FP3, we demonstrate that 3D perception is a strong ingredient for learning robot foundation models. It’s been about 1 year since we
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Geng Chen
@gengchen
Apr 26
A hierarchical policy is essential for long-horizon tasks!
Isabella Liu
@Isabella__Liu
Apr 24
VLA/VAs are doing well on short skills like pick-and-place. But real tasks rarely stop after one action, they require 1) many interdependent steps, 2) progress tracking, and 3) recovery from mistakes. In our paper LoHo-Manip, we address long-horizon manipulation with
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Geng Chen
@gengchen
Mar 23
Strongly bullish on scaling human data for robotics! Feel excited to help a bit in this ambitious project.
Danfei Xu
@danfei_xu
Mar 23
Introducing EgoVerse: an ecosystem for robot learning from egocentric human data. Built and tested by 4 research labs + 3 industry partners, EgoVerse enables both science and scaling 1300+ hrs, 240 scenes, 2000+ tasks, and growing Dataset design, findings, and ecosystem 🧵
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Geng Chen
@gengchen
Feb 11
Turning UMI-recorded end-effector trajectories into manipulation-ready humanoid whole-body actions is definitely challenging. Congrats to @RuiqianNai and team for delivering such impressive results!
Ruiqian Nai
@RuiqianNai
Feb 10
🤖 Can we demonstrate humanoid complex whole-body manipulation skills without a physical robot present? Introducing HuMI: A portable, robot-free interface for learning diverse humanoid manipulation tasks. 📄 arxiv.org/abs/2602.06643 🌐 …noid-manipulation-interface.github.io
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